Service Level Management System

ABSTRACT

A service level management (SLM) system where the system learns the structure of a web application, monitors the operation of the application, and controls the processing of incoming requests to achieve optimal performance as defined in a service level agreement (SLA). The system is operative for example in enterprise web applications and in enterprise data centers that deploy web applications and optimally is capable of controlling and maintaining a level of service of web applications.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims priority from a U.S. provisional application 60/779,706 filed on Mar. 6, 2006 which is hereby incorporated for all that it contains.

TECHNICAL FIELD

The present invention relates generally to controlling and managing the performance of web applications.

BACKGROUND OF THE INVENTION

Enterprises and organizations expose their business information and functionality on the web through software applications, usually referred to as “web applications.” Web applications provide great opportunities for an organization. Web applications use the Internet technologies and infrastructures. These applications are generally event-driven software programs which react to hyper text transfer protocol (HTTP) requests from the client. The applications are generally executed on application servers, constructed according to N-tier architecture, in which presentation, business logic, and data access layers are kept separate. Recently, web applications have evolved into large-scale applications that demand more sophisticated computing services.

FIG. 1 shows an exemplary network system 100 that is utilized for executing web applications. System 100 includes clients 110-1 through 110-N, web servers 120-1 through 120-M, application servers 130-1 through 130-Q, back-end systems 150, a load balancer 160, and a network 170. Clients 110 submit requests (e.g., HTTP requests) to web servers 120 through network 170. Load balancer 160 distributes the requests among the servers 120 to balance the load between servers 120 and 130. Each of web servers 120 dynamically generates presentation, for example, using servlets, or extensible markup language (XML), extensible style-sheet language (XSL), and the likes. Application servers 130 are often responsible for deploying and running the business logic layer and for interacting with and integrating various enterprise-wide resources, such as web servers 120, and back-end systems 150. The back-end system 150 may include, for example, a database and a legacy system.

Workload may be distributed across a cluster of application servers 130 in different ways. For example, application code may be replicated across multiple application servers in the cluster, enabling a given request to be processed by any of these multiple application servers 130. Also, application code may be logically partitioned over multiple application servers 130, e.g., so that a particular server 130 is responsible for performing particular types of operations. This type of application partitioning may improve the application performance. For example, data-intensive application logic may be configured to run on an application server that is closest to a data source, in order to reduce the latencies associated with accessing remotely located data.

As the web and application servers 120 and 130 become busier with handling more and more requests, the quality and level of service sharply decrease. With existing load balancing capabilities, once the servers are saturated, the quality of service drops drastically for all clients accessing a web site. Currently, a standard tool that automatically monitors, manages, and controls the operation and load of applications and servers is not found in the related art. The management and control of web applications mostly relies on technical personnel. This results with many drawbacks including unpredictable level of service and uncontrolled user experience as well as costly maintenance of applications. Additionally, the application management is static, i.e., the ability to detect problems and solve them in real-time is not feasible. Another major drawback is the inability to deliver services according to predefined service level agreements (SLAs), as the ability to provide committed services increasingly becomes a competitive requirement. Yet another major drawback is the inability to balance the load differently per application in servers that are installed with multiple applications.

It would be therefore advantageous to provide a network solution for automatically managing and controlling web applications that overcome the drawbacks mentioned in the prior art.

SUMMARY OF THE INVENTION

The present invention includes a service level management (SLM) system in a network with a plurality of clients and a plurality of web servers. The SLM system includes a traffic processor for processing data traffic sent from a the plurality of clients and from a the plurality of web servers; an application learner for identifying transactions sent from the plurality of clients; a monitor for monitoring and generating statistics respective of the operation of the web servers and their respective web applications; and a controller for performing corrective actions according to a plurality of predefined policies.

The present invention also includes a method for controlling and maintaining a level of service of web applications. The method includes generating a context for each request sent from a client to a web server and for each reply sent from a web server to a client; determining whether the context belongs to an identified web application; gathering statistics respective of the identified web application; determining whether at least one policy predefined for the identified application is violated; and performing a plurality of corrective actions if at least one policy is determined to be violated.

The present invention also includes a computer program product including a computer-readable medium comprising software instructions operable to enable a computer to perform a method for controlling and maintaining a level of service of web applications The program product causes a computer to execute the processes of generating a context for each request sent from a client to a web server and for each reply sent from a web server to a client; determining whether the context belongs to an identified web application; gathering statistics respective of the identified web application; determining whether at least one policy predefined for the identified application is violated; and performing a plurality of corrective actions if at least one policy is determined to be violated.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1—is a non-limiting network system utilized for executing web applications (prior art);

FIG. 2—is a diagram of a network system constructed in accordance with an exemplary embodiment of the present invention;

FIG. 3—is a block diagram of the SLM system disclosed in accordance with an embodiment of the present invention;

FIG. 4—is a flowchart describing the operation of the SLM system in accordance with an embodiment of the present invention; and

FIG. 5—is an exemplary diagram of a site tree.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 2 shows a non-limiting and exemplary diagram of a network system 200 constructed in accordance with one embodiment of the present invention. System 200 includes clients 210-1 through 210-N, web servers 220-1 through 220-M, application servers 230-1 through 230-Q connected to backend systems 250, a load balancer 260, and a network 270. System 200 further includes a service level management (SLM) system 280 that allows the maintaining of a consistent level of service of web applications. Web servers 220 process requests sent from clients and responds with the processing result. Application servers 230 execute the business logic of the web applications and communicate with back-end systems 250, which implement the data layer of the applications. In some configurations, a web server and a web application may act as a single entity, e.g., web application 230-Q. Load balancer 260 mainly distributes incoming requests to servers 220 and 230 that run the applications to which the requests are targeted.

SLM system 280 controls and manages applications executed by servers 220 and 230 in real-time, and thus ensures a committed level of service. The level of service may be defined by a service level agreement (SLA) and be different for each application. With this aim, SLM system 280 learns the structure of a web-application, monitors the operation of the application, and controls the processing of incoming requests to achieve optimal performance and level of service. In an exemplary embodiment shown in FIG. 2 SLM system 280 is configured to operate in the line of traffic, i.e., traffic passing directly through system 280 to web servers 220.

FIG. 3 shows a non-limiting block diagram of SLM system 280 disclosed in accordance with an embodiment of the present invention. SLM system 280 comprises a traffic processor 310, an application learner 320, a monitor 330, and a controller 340 connected to a common bus 350. SLM system 280 further includes databases 360 and 370 coupled to application learner 320 and a database 380 coupled to monitor 330 and controller 340. In other embodiments, SLM system 280 includes a single database commonly coupled to application learner 320, monitor 330, and controller 340.

Traffic processor 310 receives HTTP requests submitted by clients 210 as well as replies sent from servers 220 and 230 (see also FIG. 2). Specifically, once a session is established with a client 210 a client connection handler (not shown) is allocated. The client connection handler waits for data, i.e., a HTTP request submitted by a client 210, and once received, the data is sent to a parser (not shown). Both the parser and the client connection handler are part of the traffic processor 310. While processing the request, the parser returns a context of the request. A context is a joined HTTP request-reply entity. The context fields include, but are not limited to, a site name, a HTTP method, a URL, request parameters, HTTP cookies, a HTTP status code, a HTTP server, a HTTP content type, a HTTP content length, a HTML title field, and the like. The context is sent to application learner 320, monitor 330, and controller 340. The incoming request is forwarded to one of web servers 220.

When load-balance or SLM schemes are utilized by controller 340, requests may be stalled or dropped. When a reply, i.e., HTTP response is sent from a web server 230, a web server (WS) connection handler (not shown), in the traffic processor, is allocated. The WS connection handler waits until the header of the response arrives, and then forwards the header to the parser, which sends the context to application learner 320, monitor 330, and controller 340. In addition, the incoming response is sent to a client 210 through the respective client connection handler, i.e., the response is sent to the client that initiated the request.

Application learner 320 identifies web applications their transactions and modules and registers the learnt information in a classify data structure (CDS). The CDS includes a list of identified sites, for each site a list of its applications, and for each application a list transactions and modules that construct the application. A module is a group of transactions. Application learner 320 further generates for display purposes a site tree, which includes all discovered applications that belong to a designated site. The CDS is used in real-time to classify incoming requests to applications. The site tree and the CDS are saved in database 370.

FIG. 5 provides an example for a site tree. A web site 500 has two applications: a healthcare 510 and finance 520. Healthcare application 510 is composed of two applications, a patient 511 and a physician 512. Patient application 511 includes the transactions Login 511-1, Logout 511-2, View Medical Record 511-3, and Edit Profile 511-4. Physician application 512-1 includes the transactions: Login 512-1, Logout 512-2, and Edit Medical Record 512-3. Finance application 520 includes only the transactions GetQuote 520-1 and ListStocks 520-1.

Application learner 320 performs at least three tasks that include classifying, learning, and collecting. The classification includes determining, on-the-fly, for each context (i.e., parsed request) whether the incoming request belongs to a previously discovered application, and if so an application identification (ID) number is assigned to the context. Unidentified context messages may be further processed for the purpose of learning new applications and their transactions and modules. The collection task is invoked upon a reply message and it decides if the context should be collected. A context to be collected is saved, in a chronologic order, in database 360. The learning task is invoked every predefined period of time or whenever the number of collected contexts is above a predefined threshold. The learning task processes data stored in database 360 and attempts to discover a new application using a plurality of application definers and correlation processes. The application definers include conditions that are checked against context data in database 360. An example for application definers are a path of a cookie, the name of the parameter name, and so on. If one of the application definers is satisfied, then a new application is found and inserted to the CDS in an entry of the relevant site. That is, a new entry is created and the application ID together with the URL are added to the entry. In one embodiment of the present invention, the learning of applications can also be performed by correlating a plurality of saved contexts that share a common property, such URL and parameter.

Monitor 330 executes all activities related to the generation of statistics respective of the operation of the web servers and their respective applications. The statistics include, but are not limited to, measuring throughput, response time, number of errors, and so on. The statistics are kept in database 380 on a per server basis, on a per application basis, and on a per application/server combination basis. In accordance with an embodiment of the disclosed invention, a plurality of reports are produced based on the gathered statistics. These reports can be presented by means of a graphical user interface (GUI) and/or sent to a system administrator by email.

Controller 340 executes tasks that optimize the performance of each web application executed by the web and application servers. These tasks include, but are not limited to, scheduling requests to reduce response time, shaping traffic to balance the load, recovery actions when one of the servers fails, redirecting of requests, and so on. The controller's 340 tasks are performed according to a set of policies predetermined for each server, application, transaction, and module in an application. Generally, a policy defines an allowed value range for each status parameter and the actions to be taken if a status parameter is not within its range. Each policy is assigned with a priority and the time periods that the policy should be activated and the users it is relevant for. For example, a policy may define a maximum allowable latency value that is for an application and a threshold from which corrective actions should be taken. The corrective action may be, but is not limited to, the transfer of requests to a less busy server. As another example, a policy may define the minimum allowable throughput for an application and the corrective action may be stalling traffic directed to the server that executes the application. It should be noted that if a policy includes two or more corrective actions, then each of the actions may be assigned with a different priority.

FIG. 4 shows a non-limiting and exemplary flowchart 400 describing the operation of SLM system 280, in accordance with one embodiment of the present invention. At S410, an HTTP request sent from a client 210 is received at the SLM system 280. At S420, the HTTP request is parsed to generate a context of the request. At S430, the request is classified to determine whether the request belongs to a known or unknown application. This is performed by matching the context against the CDS and a plurality of classification filters and if the filtering result with an application ID, the incoming request belongs to a known (learnt) application. At S440, a check takes place to determine if an application ID was detected, and if so execution continues with S460; otherwise, executions proceeds to S445 where the context is saved in database 360. Subsequently, the context is sent to a web server 220. At S450, application learner 320 discovers the applications and preferably applications' transactions and modules related to the context. The learnt information is kept, at S455, in a CDS format in database 370.

At S460, statistics respective of the application are gathered. That is, at least the status parameters: throughput, response time, hits per second, latency and number of returned errors are measured and saved in database 380. At S470, it is checked if at least one of the policies defined for the application is violated. Namely, it is determined if the measured status parameters are within the allowed range, and if so execution proceeds to S490 where the request is sent to a web server 220; otherwise, execution continues with S480 where one or more corrective actions, as defined in the violated policy, are taken. Examples for such actions are discussed in greater detail above. The method described herein can be further utilized for processing HTTP replies sent from web servers or application servers.

The SLM system 280 and method described herein further implement a feedback mechanism. Specifically, after a corrective action is taken, SLM system 280 monitors the result of the action, i.e., whether the monitored parameters values improved due to the corrective action or actions. Accordingly, SLM system 280 updates controller 340 with the next corrective actions to activate. For example, if an action has not made a difference, this action would be less likely to be activated when subsequent request is received.

In accordance with an embodiment of the present invention, SLM system 280 tracks transactions and actual users that access the web applications in servers 220 and 230. Tracking users is performed by: a) adding a token (e.g., a cookie) to the HTTP traffic; b) identifying existing cookies that are used by existing user-management mechanisms; c) tracking SSL sessions; or d) any combination thereof. The ability to track user activity allows for identifying transactions. Specifically, SLM system 280 detects navigation routes of users, i.e., how users move between applications' transactions; compares between the detected routes; and deduces from the collected information which parts of the routes comprise independent transactions. It should be noted that not all navigation routes are considered as transactions or identified as such.

It should be noted that various modifications, combinations, sub-combinations and alterations of the above-described embodiments may occur, as required, insofar as they are within the scope of the appended claims or the equivalents thereof.

The principles of the present invention may be implemented as a combination of hardware and software. The software may be implemented as an application program tangibly embodied on a program storage unit or computer readable medium. The application program may be uploaded to, and executed by, a machine comprising any suitable architecture, for example a computer platform having hardware such as one or more central processing units (“CPU”), a random access memory (“RAM”), and input/output (“I/O”) interfaces. The computer platform may also include an operating system and microinstruction code. The various processes and functions described herein may be either part of the microinstruction code or part of the application program, or any combination thereof, which may be executed by a CPU, whether or not such computer or processor is explicitly shown.

It is to be further understood that, because some of the constituent system components and methods depicted in the accompanying drawings are preferably implemented in software, the actual connections between the system components or the process function blocks may differ depending upon the manner in which the present invention is programmed. Given the teachings herein, one of ordinary skill in the pertinent art will be able to contemplate these and similar implementations or configurations of the present invention. All examples and conditional language recited herein are intended for pedagogical purposes to aid the reader in understanding the principles of the invention and the concepts contributed by the inventors to furthering the art, and are to be construed as being without limitation to such specifically recited examples and conditions.

All statements herein reciting principles, aspects, and embodiments of the invention, as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. It is intended that such equivalents include both currently known equivalents as well as equivalents developed in the future, i.e., any elements developed that perform the same function, regardless of structure. Other hardware, conventional and/or custom, may also be included. Similarly, any switches shown in the figures are conceptual only. Their function may be carried out through the operation of program logic, through dedicated logic, through the interaction of program control and dedicated logic, or even manually, the particular technique being selectable by the implementer as more specifically understood from the context.

In the claims hereof, any element expressed as a means for performing a specified function is intended to encompass any way of performing that function including, for example, a) a combination of circuit elements that performs that function or b) software in any form, including, therefore, firmware, microcode or the like, combined with appropriate circuitry for executing that software to perform the function. The invention as defined by such claims resides in the fact that the functionalities provided by the various recited means are combined and brought together in the manner which the claims call for. Applicants thus regards any means that can provide those functionalities as equivalent to those shown herein. 

1. A service level management (SLM) system in a network with a plurality of clients and a plurality of web servers, the SLM system comprising: a traffic processor for processing data traffic sent from the plurality of clients and from the plurality of web servers; an application learner for identifying transactions sent from the plurality of clients; a monitor for monitoring and generating statistics respective of the operation of the web servers and their respective web applications; and a controller for performing corrective actions according to a plurality of predefined policies.
 2. The SLM system of claim 1, further comprising a common bus for providing a communication medium between the traffic processor, the application learner, the monitor, and the controller.
 3. The SLM system of claim 1, wherein the traffic sent from the clients including at least hypertext transfer protocol (HTTP) requests.
 4. The SLM system of claim 3, wherein the traffic sent from the plurality of web servers including at least HTTP replies.
 5. The SLM system of claim 5, wherein the application learner further including: discovering transactions executed by the plurality of web servers; classifying incoming requests to discovered web applications; collecting non-classified incoming requests; and generating a site tree.
 6. The SLM system of claim 5, wherein the site tree includes all identified applications, transactions and modules that belong to a designate web site.
 7. The SLM system of claim 5, wherein the collected incoming requests are saved in a first database coupled to the application learner.
 8. The SLM system of claim 7, wherein discovering the transactions including: processing requests saved in the first database using at least a plurality of application definers; and saving information related to the discovered web applications in a classify data structure (CDS).
 9. The SLM system of claim 10, wherein the CDS includes a list of identified sites, for each site a list of its web applications, and for each web application a list transactions and modules that construct the web application.
 10. The SLM system of claim 3, wherein the CDS is saved in a database, wherein the database is coupled to the application learner.
 11. The SLM system of claim 1, wherein the statistics respective of the operation of the web servers are generated for each web application and include at least one of the following measures: throughput, response time, number of errors, hits per second, and latency.
 12. The SLM system of claim 11, wherein the generated statistics are saved in a database, wherein the database is coupled to the monitor.
 13. The SLM system of claim 1, wherein the monitor is further producing a plurality of reports based on the generated statistics.
 14. The SLM system of claim 1, wherein the corrective actions including at least one of: scheduling requests to reduce response time, shaping traffic to balance the load, and recovery actions on web servers.
 15. The SLM system of claim 14, wherein each of the plurality of predefined policies defines at least one corrective action to be performed.
 16. The SLM system of claim 15, wherein a policy is determined for a web server, a web application, a module and a transaction.
 17. The SLM system of claim 15, wherein each policy is assigned with a priority and time periods to be activated.
 18. The SLM system of claim 1 is configured to operate in series with data traffic and for controlling and maintaining a level of service of web applications.
 19. A method for controlling and maintaining a level of service of web applications, comprising: generating a context for each request sent from a client to a web server and for each reply sent from a web server to a client; determining whether the context belongs to an identified transaction; gathering statistics respective of the identified transaction; determining whether at least one policy predefined for the identified application is violated; and performing a plurality of corrective actions if at least one policy is determined to be violated.
 20. The method of claim 19, further comprising: saving the context in a database if it is determined that the context does not belong to an identified transaction; and learning new applications using data stored in the database.
 21. The method of claim 20, wherein the learning of the new applications is performed using at least one of: an application definer, and a correlation process.
 22. The method of claim 21, wherein learning new applications further comprising: discovering transactions and modules that construct each of the web applications; and generating a site tree.
 23. The method of claim 22, wherein the request is at least a hypertext transfer protocol (HTTP) request.
 24. The method of claim 23, wherein generating the context includes parsing the HTTP request.
 25. The method of claim 23, wherein determining if the context belongs to an identified transaction, comprising: matching the context against a classify data structure (CDC) and a plurality of application filters.
 26. The method of claim 25, wherein the CDC including: a list of identified sites, for each site a list of its web applications, and for each web application a list of transactions and modules that construct the web application.
 27. The method of claim 26, wherein the gathered statistics include measures on at least one of: throughput, response time, number of errors, hits per second, and latency.
 28. The method of claim 19, wherein the step of gathering statistics further comprising: producing a plurality of reports based on the gather statistics.
 29. The method of claim 19, wherein the at least one policy is checked against the gathered statistics.
 30. The method of claim 29, wherein the at least one policy defines at least one corrective action to be performed.
 31. The method of claim 30, wherein a policy is determined for a web server, a web application, a module, and a transaction.
 32. The method of claim 31, wherein the corrective actions include at least one of: scheduling requests to reduce response time, shaping traffic to balance the load, and recovery actions on web servers.
 33. The method of claim 19 is configured to operate in the line of traffic.
 34. A computer program product including a computer-readable medium comprising software instructions operable to enable a computer to perform a method for controlling and maintaining a level of service of web applications, comprising: generating a context for each request sent from a client to a web server and for each reply sent from a web server to a client; determining whether the context belongs to an identified web application; gathering statistics respective of the identified transaction; determining whether at least one policy predefined for the transaction is violated; and performing a plurality of corrective actions if at least one policy is determined to be violated.
 35. The computer program product of claim 34, further comprising: saving the context in a database if it is determined that the context does not belong to an transaction application; learning new applications using data stored in the database.
 36. The computer program product of claim 35, wherein learning of the new applications is performed using at least one of: an application definer, and a correlation process.
 37. The computer program product of claim 36, wherein learning new applications further comprising: discovering transactions and modules that construct each of the web applications; and generating a site tree.
 38. The computer program product of claim 37, wherein the request is at least a hypertext transfer protocol (HTTP) request.
 39. The computer program product of claim 38, wherein generating the context includes parsing the HTTP request.
 40. The computer program product of claim 38, wherein determining if the context belongs to an identified transaction, comprising: matching the context against a classify data structure (CDC) and a plurality of application filters.
 41. The computer program product of claim 40, wherein the CDC including: a list of identified sites, for each site a list of its web applications, and for each web application a list of transactions and modules that construct the web application.
 42. The computer program product of claim 41, wherein the gathered statistics include measures on at least one of: throughput, response time, number of errors, hits per second, and latency.
 43. The computer program product of claim 34, wherein the step of gathering statistics further comprising: producing a plurality of reports based on the gather statistics.
 44. The computer program product of claim 34, wherein the at least one policy is checked against the gathered statistics.
 45. The computer program product of claim 44, wherein the at least one policy defines at least one corrective action to be performed.
 46. The computer program product of claim 45, wherein a policy is determined for a web server, a web application, a module, and a transaction.
 47. The computer program product of claim 46, wherein the corrective actions include at least one of: scheduling requests to reduce response time, shaping traffic to balance the load, and recovery actions on web servers.
 48. The computer program product of claim 34 is configured for execution on a controller operating in series with data traffic.
 49. A service level management (SLM) system installed in series with data traffic between a plurality of clients and a plurality of web servers, the SLM system comprising: a traffic processor for processing data traffic sent from the plurality of clients and from the plurality of web servers; an application learner for identifying transactions sent from the plurality of clients; a monitor for monitoring and generating statistics respective of the operation of the web servers and their respective web applications; and a controller for performing corrective actions according to a plurality of predefined policies. 